steam_reviews
List reviews for a Steam app. Returns a page of user reviews for an app with cursor pagination and an aggregate query_summary (score, positive/negative totals). Aggregate totals populate only on the first page (cursor=*). Pass the returned cursor back to page. Credential-free public Steam storefr...
This record as markdown: /tools/crawlora-mcp/steam-reviews.md
What steam_reviews does on Crawlora
AI agents call steam_reviews to retrieve information from Crawlora without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
appid | string | Yes | Numeric Steam app id |
cursor | string | — | Pagination cursor from the previous page |
filter | string | — | Sort order |
language | string | — | Steam language name or 'all' |
day_range | integer | — | Look-back window in days (filter=all only, max 365) |
review_type | string | — | Review sentiment filter |
num_per_page | integer | — | Reviews per page (max 100) |
purchase_type | string | — | Purchase source filter |
Parameters from the server's own tool schema.
Why steam_reviews is rated Low
This tool retrieves publicly available review data from Steam's storefront with pagination support. There are no side effects, no data modification, no code execution, and no destructive operations. It is purely a read operation that queries existing public data. The low severity reflects that misuse (e.g., scraping reviews at scale) causes minimal direct harm compared to other tool categories.
From the tool's definition Tool description explicitly states it 'List reviews for a Steam app' and 'Returns a page of user reviews' from 'Credential-free public Steam storefront JSON'. The verb 'List' and 'Returns' indicate data retrieval with no modification capability.
Attacks that exploit this kind of access
The rule that runs steam_reviews safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Crawlora, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For steam_reviews, this is the rule to start with:
steam_reviews is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Crawlora, apply this rule, and every steam_reviews call is checked against it from then on.
Questions about steam_reviews
List reviews for a Steam app. Returns a page of user reviews for an app with cursor pagination and an aggregate query_summary (score, positive/negative totals). Aggregate totals populate only on the first page (cursor=*). Pass the returned cursor back to page. Credential-free public Steam storefront JSON. It is categorised as a Read tool in the Crawlora MCP Server, which means it retrieves data without modifying state.
steam_reviews accepts 8 parameters: appid, cursor, filter, language, day_range, review_type, num_per_page, purchase_type. Required: appid. The full parameter table on this page comes from the server's own tool schema.
Register the Crawlora MCP server in PolicyLayer and add a rule for steam_reviews: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Crawlora. Nothing to install.
steam_reviews is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the steam_reviews rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for steam_reviews. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
steam_reviews is provided by the Crawlora MCP server (crawlora-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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